Dynamics of Resolved Polar Clouds

• Main Author: Zhang, Xiyue
• Format: Thesis
• Language: English
• Published: California Institute of Technology 2018
• Subjects: Climate change; Cloud dynamics; Environmental Science and Engineering; polar climate; Arctic; polar night; Sea ice
• Online Access: https://dx.doi.org/10.7907/69e7-0q10; https://resolver.caltech.edu/CaltechTHESIS:05312018-154833107

The polar regions have been experiencing rapid warming and ice loss as greenhouse gas concentrations have risen. The projected warming in the Arctic varies significantly across climate models, part of which is attributed to polar cloud feedbacks. This thesis addresses the question of what drives the changes in polar clouds as the climate warms, using a large eddy simulation (LES) model. LES is a powerful high-resolution model that resolves the most energetic turbulence relevant for clouds. First, we focus on the Arctic boundary layer clouds through three observation based case studies. The cloud and boundary layer characteristics simulated by the LES agree reasonably well with observations and model intercomparisons. We found that during polar night over sea ice, cloud water path increases with temperature and free-tropospheric relative humidity, but it decreases with inversion strength across the cloud top. Most of these changes can be explained by a mixed-layer model. The strength of the estimated positive cloud longwave feedback largely depends on the cloud top inversion strength. Next, we extend the LES domain to cover the entire polar troposphere, and use output from an idealized GCM as forcing to drive the LES. This novel framework allows changes in the large-scale circulation to be parameterized in the LES. The simulated seasonal cycle of liquid clouds resembles observations. In a warmer climate, there is a significant decrease of the low-level liquid clouds during summer and autumn. In spring and winter, liquid clouds increase at all levels. Both the liquid and ice cloud tops rise as the climate warms. Offline radiative transfer calculations estimate a positive cloud feedback that is dominated by longwave feedback.